Introduction: LIH Department DII

Here are preliminary results of the bibliometric mapping of the 2022 Luxembourg research evaluation. Its purpose is:

The method for the research-field-mapping can be reviewed here:

Rakas, M., & Hain, D. S. (2019). The state of innovation system research: What happens beneath the surface?. Research Policy, 48(9), 103787.

Seed Articles

The seed articles deemed representative for the active areas of research in the institution, and include authors affiliated with the institution. They can be selected in three ways:

  1. Via bibliographic clustering of the institutions publications and selection of most central articles per cluster (only clsuters where n >= 0.05N). Selection can be found at: https://github.com/daniel-hain/biblio_lux_2022/blob/master/output/seed/scopus_lih_dii_seed.csv
  2. Manual selection of relevant publications.
  3. A combination of 1. and 2.

The present analysis is based on the following seed articles:

AU PY TI JI
ELWENSPOEK MMC;HENGESCH X;L… 2020 GLUCOCORTICOID RECEPTOR SIGNALING IN LEUKOCYTES AFTER EARLY LIFE ADVERSITY DEV. PSYCHOPATHOL.
KURNIAWAN H;FRANCHINA DG;GU… 2020 GLUTATHIONE RESTRICTS SERINE METABOLISM TO PRESERVE REGULATORY T CELL FUNCTION CELL METAB.
BÜRCKERT J-P;FAISON WJ;MUST… 2018 HIGH-THROUGHPUT SEQUENCING OF MURINE IMMUNOGLOBULIN HEAVY CHAIN REPERTOIRES USING SINGLE SIDE UNI… ONCOTARGET
SZPAKOWSKA M;MEYRATH M;REYN… 2018 MUTATIONAL ANALYSIS OF THE EXTRACELLULAR DISULPHIDE BRIDGES OF THE ATYPICAL CHEMOKINE RECEPTOR AC… BIOCHEM. PHARMACOL.
BLANK S;BILÒ MB;OLLERT M 2018 COMPONENT-RESOLVED DIAGNOSTICS TO DIRECT IN VENOM IMMUNOTHERAPY: IMPORTANT STEPS TOWARDS PRECISIO… CLIN. EXP. ALLERGY
MUÑOZ-ALÍA MÁ;MULLER CP;RUS… 2017 ANTIGENIC DRIFT DEFINES A NEW D4 SUBGENOTYPE OF MEASLES VIRUS J. VIROL.
KUEHN A;DICKEL H 2016 FISH AND SEAFOOD ALLERGY [ALLERGIEN AUF MEERESTIERE] ALLERGOLOGIE
MORISSET M;ARUMUGAM K;OLLER… 2016 HORSE-MEAT ALLERGY MEDIATED BY DOG-ALLERGY: A CASE REPORT AND REVIEW OF THE LITERATURE ALLERGO J.

Topic modelling

Here, we report the results of a LDA topic-modelling (basically, clustering on words) on all title+abstract texts.

Topics by topwords

Note: While this static vies is helpful, I recommend using the interactive LDAVis version to be found under https://daniel-hain.github.io/biblio_lux_2022/output/topic_modelling/LDAviz_lih_dii.rds/index.html#topic=1&lambda=0.60&term=. For functionality and usage, see technical description in the next tab.

Topics over time

Technical Description

LDA Topic Modelling

Topic modeling is a type of statistical modeling for discovering the abstract “topics” that occur in a collection of documents. Latent Dirichlet Allocation (LDA, Blei et al., 2003) is an example of topic model and is used to classify text in a document to a particular topic.

LDA is a generative probabilistic model that assumes each topic is a mixture over an underlying set of words, and each document is a mixture of over a set of topic probabilities. It builds a topic per document model and words per topic model, modeled as Dirichlet distributions.

LDAVis

LDAvis is a web-based interactive visualisation of topics estimated using LDA (Sievert & Shirley, 2014). It provides a global view of the topics (and how they differ from each other), while at the same time allowing for a deep inspection of the terms most highly associated with each individual topic. The package extracts information from a fitted LDA topic model to inform an interactive web-based visualization. The visualisation has two basic pieces.

The left panel visualise the topics as circles in the two-dimensional plane whose centres are determined by computing the Jensen–Shannon divergence between topics, and then by using multidimensional scaling to project the inter-topic distances onto two dimensions. Each topic’s overall prevalence is encoded using the areas of the circles.

The right panel depicts a horizontal bar chart whose bars represent the individual terms that are the most useful for interpreting the currently selected topic on the left. A pair of overlaid bars represent both the corpus-wide frequency of a given term as well as the topic-specific frequency of the term.

The \(\lambda\) slider allows to rank the terms according to term relevance. By default, the terms of a topic are ranked in decreasing order according their topic-specific probability ( \(\lambda\) = 1 ). Moving the slider allows to adjust the rank of terms based on much discriminatory (or “relevant”) are for the specific topic. The suggested optimal value of \(\lambda\) is 0.6.

Knowledge Bases: Co-Citation network analysis

Note: This analysis refers the co-citation analysis, where the cited references and not the original publications are the unit of analysis. See tab Technical descriptionfor additional explanations

Knowledge Bases summary

In order to partition networks into components or clusters, we deploy a community detection technique based on the Lovain Algorithm (Blondel et al., 2008). The Lovain Algorithm is a heuristic method that attempts to optimize the modularity of communities within a network by maximizing within- and minimizing between-community connectivity. We identify the following communities = knowledge bases.

name dgr_int dgr
Knowledge Base 1: KB 1: unlabeled (n = 1882, density =2.07)
TYRKA A.R. PRICE L.H. MARSIT C. WALTERS O.C. CARPENTER L.L. CHILDHOOD ADVERSITY AND EPIGENETIC MODULATION OF THE LEUKOCYTE GLUCOCORTICOID RECEPTOR:… 2082 2082
OBERLANDER T.F. WEINBERG J. PAPSDORF M. GRUNAU R. MISRI S. DEVLIN A.M. PRENATAL EXPOSURE TO MATERNAL DEPRESSION NEONATAL METHYLATION OF HUMAN GLUCO… 1980 1980
TURECKI G. MEANEY M.J. EFFECTS OF THE SOCIAL ENVIRONMENT AND STRESS ON GLUCOCORTICOID RECEPTOR GENE METHYLATION: A SYSTEMATIC REVIEW (2016) 1787 1791
ROTH T.L. LUBIN F.D. FUNK A.J. SWEATT J.D. LASTING EPIGENETIC INFLUENCE OF EARLY-LIFE ADVERSITY ON THE BDNF GENE (2009) 1396 1396
ROMENS S.E. MCDONALD J. SVAREN J. POLLAK S.D. ASSOCIATIONS BETWEEN EARLY LIFE STRESS AND GENE METHYLATION IN CHILDREN (2015) 867 867
LUPIEN S.J. MCEWEN B.S. GUNNAR M.R. HEIM C. EFFECTS OF STRESS THROUGHOUT THE LIFESPAN ON THE BRAIN BEHAVIOUR AND COGNITION (2009) 836 836
BINDER E.B. THE ROLE OF FKBP5 A CO-CHAPERONE OF THE GLUCOCORTICOID RECEPTOR IN THE PATHOGENESIS AND THERAPY OF AFFECTIVE AND ANXIETY DISORDERS (2009) 661 661
WEAVER I.C. CERVONI N. CHAMPAGNE F.A. D’ALESSIO A.C. SHARMA S. SECKL J.R. DYMOV S. MEANEY M.J. EPIGENETIC PROGRAMMING BY MATERNAL BEHAVIOR (2004) 637 637
JONES P.A. FUNCTIONS OF DNA METHYLATION: ISLANDS START SITES GENE BODIES AND BEYOND (2012) 628 628
MCGOWAN P.O. SASAKI A. D’ALESSIO A.C. EPIGENETIC REGULATION OF THE GLUCOCORTICOID RECEPTOR IN HUMAN BRAIN ASSOCIATES WITH CHILDHOOD ABUSE (2009) 594 594
Knowledge Base 2: KB 2: unlabeled (n = 762, density =4.27)
LEVOYE A. BALABANIAN K. BALEUX F. BACHELERIE F. LAGANE B. CXCR7 HETERODIMERIZES WITH CXCR4 AND REGULATES CXCL12-MEDIATED G PROTEIN SIGNALING (2009) 2364 2364
DISSOCIATION OF CXCR4 ACTIVATION FROM BINDING AND INHIBITION OF HIV-1 (1997) 1799 1799
LUKER K.E. STEELE J.M. MIHALKO L.A. RAY P. LUKER G.D. CONSTITUTIVE AND CHEMOKINE-DEPENDENT INTERNALIZATION AND RECYCLING OF CXCR7 IN BREAST CANCER … 923 926
BURNS J.M. SUMMERS B.C. WANG Y. MELIKIAN A. BERAHOVICH R. MIAO Z. A NOVEL CHEMOKINE RECEPTOR FOR SDF-1 AND I-TAC INVOLVED IN CELL SURVIVAL CELL ADH… 918 918
BUSILLO J.M. BENOVIC J.L. REGULATION OF CXCR4 SIGNALING (2007) 817 817
BALKWILL F. CANCER AND THE CHEMOKINE NETWORK (2004) 794 804
ZLOTNIK A. YOSHIE O. THE CHEMOKINE SUPERFAMILY REVISITED (2012) 784 784
TEICHER B.A. FRICKER S.P. CXCL12 (SDF-1) 779 782
KALATSKAYA I. BERCHICHE Y.A. GRAVEL S. LIMBERG B.J. ROSENBAUM J.S. HEVEKER N. AMD3100 IS A CXCR7 LIGAND WITH ALLOSTERIC AGONIST PROPERTIES (2009) 749 749
GRIFFITH J.W. SOKOL C.L. LUSTER A.D. CHEMOKINES AND CHEMOKINE RECEPTORS: POSITIONING CELLS FOR HOST DEFENSE AND IMMUNITY (2014) 711 711
Knowledge Base 3: KB 3: unlabeled (n = 1714, density =2.53)
GUPTA R.S. SPRINGSTON E.E. WARRIER M.R. SMITH B. KUMAR R. PONGRACIC J. THE PREVALENCE SEVERITY AND DISTRIBUTION OF CHILDHOOD FOOD ALLERGY IN THE UN… 1020 1047
BOCK S.A. MUNOZ-FURLONG A. SAMPSON H.A. FATALITIES DUE TO ANAPHYLACTIC REACTIONS TO FOODS (2001) 988 1001
SAMPSON H.A. UTILITY OF FOOD-SPECIFIC IGE CONCENTRATIONS IN PREDICTING SYMPTOMATIC FOOD ALLERGY (2001) 975 1050
SICHERER S.H. SAMPSON H.A. FOOD ALLERGY: EPIDEMIOLOGY PATHOGENESIS DIAGNOSIS AND TREATMENT (2014) 908 1095
DU TOIT G. ROBERTS G. SAYRE P.H. BAHNSON H.T. RADULOVIC S. SANTOS A.F. RANDOMIZED TRIAL OF PEANUT CONSUMPTION IN INFANTS AT RISK FOR PEANUT ALLERGY… 895 945
MURARO A. WERFEL T. HOFFMANN-SOMMERGRUBER K. EAACI FOOD ALLERGY AND ANAPHYLAXIS GUIDELINES: DIAGNOSIS AND MANAGEMENT OF FOOD ALLERGY (2014) 869 935
SICHERER S.H. SAMPSON H.A. FOOD ALLERGY (2010) 836 1275
BOCK S.A. MUÑOZ-FURLONG A. SAMPSON H.A. FATALITIES DUE TO ANAPHYLACTIC REACTIONS TO FOODS (2001) 794 811
SAMPSON H.A. MENDELSON L. ROSEN J.P. FATAL AND NEAR-FATAL ANAPHYLACTIC REACTIONS TO FOOD IN CHILDREN AND ADOLESCENTS (1992) 602 610
MURARO A. WERFEL T. HOFFMANN-SOMMERGRUBER K. ROBERTS G. BEYER K. BINDSLEV-JENSEN C. EAACI FOOD ALLERGY AND ANAPHYLAXIS GUIDELINES: DIAGNOSIS AND MA… 523 537
Knowledge Base 4: KB 4: unlabeled (n = 1591, density =2.74)
MACIVER N.J. MICHALEK R.D. RATHMELL J.C. METABOLIC REGULATION OF T LYMPHOCYTES (2013) 2484 2704
MICHALEK R.D. GERRIETS V.A. JACOBS S.R. MACINTYRE A.N. MACIVER N.J. MASON E.F. SULLIVAN S.A. RATHMELL J.C. CUTTING EDGE: DISTINCT GLYCOLYTIC AND LI… 2158 2492
ZENG H. YANG K. CLOER C. NEALE G. VOGEL P. CHI H. MTORC1 COUPLES IMMUNE SIGNALS AND METABOLIC PROGRAMMING TO ESTABLISH T(REG) 2017 2976
SHI L.Z. WANG R. HUANG G. VOGEL P. NEALE G. GREEN D.R. HIF1ALPHA-DEPENDENT GLYCOLYTIC PATHWAY ORCHESTRATES A METABOLIC CHECKPOINT FOR THE DIFFERENT… 1568 2001
PEARCE E.L. POFFENBERGER M.C. CHANG C.H. JONES R.G. FUELING IMMUNITY: INSIGHTS INTO METABOLISM AND LYMPHOCYTE FUNCTION (2013) 1563 1811
SHI L.Z. WANG R. HUANG G. VOGEL P. NEALE G. GREEN D.R. CHI H. HIF1ALPHA-DEPENDENT GLYCOLYTIC PATHWAY ORCHESTRATES A METABOLIC CHECKPOINT FOR THE DI… 1522 1738
SINCLAIR L.V. ROLF J. EMSLIE E. SHI Y.B. TAYLOR P.M. CANTRELL D.A. CONTROL OF AMINO-ACID TRANSPORT BY ANTIGEN RECEPTORS COORDINATES THE METABOLIC R… 1519 1678
PENG M. YIN N. CHHANGAWALA S. XU K. LESLIE C.S. LI M.O. AEROBIC GLYCOLYSIS PROMOTES T HELPER 1 CELL DIFFERENTIATION THROUGH AN EPIGENETIC MECHANISM… 1503 1651
MICHALEK R.D. GERRIETS V.A. JACOBS S.R. MACINTYRE A.N. MACIVER N.J. MASON E.F. CUTTING EDGE: DISTINCT GLYCOLYTIC AND LIPID OXIDATIVE METABOLIC PROG… 1425 1729
WANG R. DILLON C.P. SHI L.Z. MILASTA S. CARTER R. FINKELSTEIN D. THE TRANSCRIPTION FACTOR MYC CONTROLS METABOLIC REPROGRAMMING UPON T LYMPHOCYTE AC… 1377 1500
Knowledge Base 5: KB 5: unlabeled (n = 1332, density =6.19)
HORI S. NOMURA T. SAKAGUCHI S. CONTROL OF REGULATORY T CELL DEVELOPMENT BY THE TRANSCRIPTION FACTOR FOXP3 (2003) 6131 6639
FONTENOT J.D. GAVIN M.A. RUDENSKY A.Y. FOXP3 PROGRAMS THE DEVELOPMENT AND FUNCTION OF CD4+CD25+ REGULATORY T CELLS (2003) 4874 5289
ZHENG Y. JOSEFOWICZ S. CHAUDHRY A. PENG X.P. FORBUSH K. RUDENSKY A.Y. ROLE OF CONSERVED NON-CODING DNA ELEMENTS IN THE FOXP3 GENE IN REGULATORY T-C… 1820 2064
SAKAGUCHI S. SAKAGUCHI N. ASANO M. ITOH M. TODA M. IMMUNOLOGIC SELF-TOLERANCE MAINTAINED BY ACTIVATED T CELLS EXPRESSING IL-2 RECEPTOR ALPHA-CHAINS… 1629 1890
KHATTRI R. COX T. YASAYKO S.A. RAMSDELL F. AN ESSENTIAL ROLE FOR SCURFIN IN CD4+CD25+ T REGULATORY CELLS (2003) 1527 1577
JOSEFOWICZ S.Z. LU L.F. RUDENSKY A.Y. REGULATORY T CELLS: MECHANISMS OF DIFFERENTIATION AND FUNCTION (2012) 1485 1660
SAKAGUCHI S. YAMAGUCHI T. NOMURA T. ONO M. REGULATORY T CELLS AND IMMUNE TOLERANCE (2008) 1266 1345
SHRESTHA S. YANG K. GUY C. VOGEL P. NEALE G. CHI H. TREG CELLS REQUIRE THE PHOSPHATASE PTEN TO RESTRAIN TH1 AND TFH CELL RESPONSES (2015) 1226 2316
LI X. LIANG Y. LEBLANC M. BENNER C. ZHENG Y. FUNCTION OF A FOXP3 CIS-ELEMENT IN PROTECTING REGULATORY T CELL IDENTITY (2014) 1218 1322
FENG Y. ARVEY A. CHINEN T. VAN DER VEEKEN J. GASTEIGER G. RUDENSKY A.Y. CONTROL OF THE INHERITANCE OF REGULATORY T CELL IDENTITY BY A CIS ELEMENT I… 968 1079
Knowledge Base 6: KB 6: unlabeled (n = 1320, density =5.2)
LOCASALE J.W. SERINE GLYCINE AND ONE-CARBON UNITS: CANCER METABOLISM IN FULL CIRCLE (2013) 2520 2617
DUCKER G.S. RABINOWITZ J.D. ONE-CARBON METABOLISM IN HEALTH AND DISEASE (2017) 1726 1798
POSSEMATO R. MARKS K.M. SHAUL Y.D. PACOLD M.E. KIM D. BIRSOY K. SETHUMADHAVAN S. JHA A.K. FUNCTIONAL GENOMICS REVEAL THAT THE SERINE SYNTHESIS PATH… 1669 1715
LOCASALE J.W. GRASSIAN A.R. MELMAN T. LYSSIOTIS C.A. MATTAINI K.R. BASS A.J. HEFFRON G. SHARFI H. PHOSPHOGLYCERATE DEHYDROGENASE DIVERTS GLYCOLYTIC… 1664 1718
FAN J. YE J. KAMPHORST J.J. SHLOMI T. THOMPSON C.B. RABINOWITZ J.D. QUANTITATIVE FLUX ANALYSIS REVEALS FOLATE-DEPENDENT NADPH PRODUCTION (2014) 1521 1565
TIBBETTS A.S. APPLING D.R. COMPARTMENTALIZATION OF MAMMALIAN FOLATE-MEDIATED ONE-CARBON METABOLISM (2010) 1494 1517
MADDOCKS O.D. BERKERS C.R. MASON S.M. ZHENG L. BLYTH K. GOTTLIEB E. VOUSDEN K.H. SERINE STARVATION INDUCES STRESS AND P53-DEPENDENT METABOLIC REMOD… 1331 1358
LABUSCHAGNE C.F. VAN DEN BROEK N.J. MACKAY G.M. VOUSDEN K.H. MADDOCKS O.D. SERINE BUT NOT GLYCINE SUPPORTS ONE-CARBON METABOLISM AND PROLIFERATION … 1239 1258
HANAHAN D. WEINBERG R.A. HALLMARKS OF CANCER: THE NEXT GENERATION (2011) 1237 1559
YANG M. VOUSDEN K.H. SERINE AND ONE-CARBON METABOLISM IN CANCER (2016) 1214 1279
Knowledge Base 7: KB 7: unlabeled (n = 1194, density =6.12)
GEORGIOU G. IPPOLITO G.C. BEAUSANG J. BUSSE C.E. WARDEMANN H. QUAKE S.R. THE PROMISE AND CHALLENGE OF HIGH-THROUGHPUT SEQUENCING OF THE ANTIBODY RE… 1645 1691
YE J. MA N. MADDEN T.L. OSTELL J.M. IGBLAST: AN IMMUNOGLOBULIN VARIABLE DOMAIN SEQUENCE ANALYSIS TOOL (2013) 1170 1205
VOLLMERS C. SIT R.V. WEINSTEIN J.A. DEKKER C.L. QUAKE S.R. GENETIC MEASUREMENT OF MEMORY B-CELL RECALL USING ANTIBODY REPERTOIRE SEQUENCING (2013) 1101 1150
YAARI G. KLEINSTEIN S.H. PRACTICAL GUIDELINES FOR B-CELL RECEPTOR REPERTOIRE SEQUENCING ANALYSIS (2015) 1095 1132
TONEGAWA S. SOMATIC GENERATION OF ANTIBODY DIVERSITY (1983) 966 985
GADALA-MARIA D. YAARI G. UDUMAN M. KLEINSTEIN S.H. AUTOMATED ANALYSIS OF HIGH-THROUGHPUT B-CELL SEQUENCING DATA REVEALS A HIGH FREQUENCY OF NOVEL I… 735 751
GREIFF V. MIHO E. MENZEL U. REDDY S.T. BIOINFORMATIC AND STATISTICAL ANALYSIS OF ADAPTIVE IMMUNE REPERTOIRES (2015) 652 657
BOLOTIN D.A. POSLAVSKY S. MITROPHANOV I. SHUGAY M. MAMEDOV I.Z. PUTINTSEVA E.V. MIXCR: SOFTWARE FOR COMPREHENSIVE ADAPTIVE IMMUNITY PROFILING (2015) 646 655
SHUGAY M. BRITANOVA O.V. MERZLYAK E.M. TURCHANINOVA M.A. MAMEDOV I.Z. TUGANBAEV T.R. TOWARDS ERROR-FREE PROFILING OF IMMUNE REPERTOIRES (2014) 626 644
FREEMAN J.D. WARREN R.L. WEBB J.R. NELSON B.H. HOLT R.A. PROFILING THE T-CELL RECEPTOR BETA-CHAIN REPERTOIRE BY MASSIVELY PARALLEL SEQUENCING (2009) 615 618
Knowledge Base 8: KB 8: unlabeled (n = 993, density =4.21)
SHARP M.F. LOPATA A.L. FISH ALLERGY: IN REVIEW (2014) 611 699
VAN DO T. ELSAYED S. FLORVAAG E. HORDVIK I. ENDRESEN C. ALLERGY TO FISH PARVALBUMINS: STUDIES ON THE CROSS-REACTIVITY OF ALLERGENS FROM 9 COMMONLY … 513 536
RADAUER C. BUBLIN M. WAGNER S. MARI A. BREITENEDER H. ALLERGENS ARE DISTRIBUTED INTO FEW PROTEIN FAMILIES AND POSSESS A RESTRICTED NUMBER OF BIOCHE… 501 580
KUEHN A. SWOBODA I. ARUMUGAM K. HILGER C. HENTGES F. FISH ALLERGENS AT A GLANCE: VARIABLE ALLERGENICITY OF PARVALBUMINS THE MAJOR FISH ALLERGENS (2… 423 444
AYUSO R. LEHRER S.B. REESE G. IDENTIFICATION OF CONTINUOUS ALLERGENIC REGIONS OF THE MAJOR SHRIMP ALLERGEN PEN A 1 (TROPOMYOSIN) 410 434
LIU R. HOLCK A.L. YANG E. LIU C. XUE W. TROPOMYOSIN FROM TILAPIA (OREOCHROMIS MOSSAMBICUS) 381 394
AYUSO R. REESE G. LEONG-KEE S. PLANTE M. LEHRER S.B. MOLECULAR BASIS OF ARTHROPOD CROSS-REACTIVITY: IGE-BINDING CROSS-REACTIVE EPITOPES OF SHRIMP H… 365 381
YU C.J. LIN Y.F. CHIANG B.L. CHOW L.P. PROTEOMICS AND IMMUNOLOGICAL ANALYSIS OF A NOVEL SHRIMP ALLERGEN PEN M 2 (2003) 361 370
KUEHN A. SCHEUERMANN T. HILGER C. HENTGES F. IMPORTANT VARIATIONS IN PARVALBUMIN CONTENT IN COMMON FISH SPECIES: A FACTOR POSSIBLY CONTRIBUTING TO … 361 375
REESE G. AYUSO R. LEHRER S.B. TROPOMYOSIN: AN INVERTEBRATE PAN-ALLERGEN (1999) 342 385
Knowledge Base 9: KB 9: unlabeled (n = 792, density =4.04)
MATRICARDI P.M. KLEINE-TEBBE J. HOFFMANN H.J. EAACI MOLECULAR ALLERGOLOGY USER’S GUIDE (2016) 645 907
MATRICARDI P.M. KLEINE-TEBBE J. HOFFMANN H.J. VALENTA R. HILGER C. HOFMAIER S. EAACI MOLECULAR ALLERGOLOGY USER’S GUIDE (2016) 411 630
ROBERTS G. PFAAR O. AKDIS C.A. EAACI GUIDELINES ON ALLERGEN IMMUNOTHERAPY: ALLERGIC RHINOCONJUNCTIVITIS (2018) 389 389
VALENTA R. CAMPANA R. FOCKE-TEJKL M. NIEDERBERGER V. VACCINE DEVELOPMENT FOR ALLERGEN-SPECIFIC IMMUNOTHERAPY BASED ON RECOMBINANT ALLERGENS AND SYN… 345 354
LUPINEK C. WOLLMANN E. BAAR A. BANERJEE S. BREITENEDER H. BROECKER B.M. ADVANCES IN ALLERGEN-MICROARRAY TECHNOLOGY FOR DIAGNOSIS AND MONITORING OF … 339 342
JUTEL M. JAEGER L. SUCK R. MEYER H. FIEBIG H. CROMWELL O. ALLERGEN-SPECIFIC IMMUNOTHERAPY WITH RECOMBINANT GRASS POLLEN ALLERGENS (2005) 313 313
SHAMJI M.H. KAPPEN J.H. AKDIS M. BIOMARKERS FOR MONITORING CLINICAL EFFICACY OF ALLERGEN IMMUNOTHERAPY FOR ALLERGIC RHINOCONJUNCTIVITIS AND ALLERGI… 310 310
NOON L. PROPHYLACTIC INOCULATION AGAINST HAY FEVER (1911) 299 321
PAJNO G.B. FERNANDEZ-RIVAS M. ARASI S. EAACI GUIDELINES ON ALLERGEN IMMUNOTHERAPY: IGE-MEDIATED FOOD ALLERGY (2018) 298 383
LUPINEK C. WOLLMANN E. BAAR A. ADVANCES IN ALLERGEN-MICROARRAY TECHNOLOGY FOR DIAGNOSIS AND MONITORING OF ALLERGY: THE MEDALL ALLERGEN-CHIP (2014) 291 316
Knowledge Base 10: KB 10: unlabeled (n = 791, density =5.36)
TAMURA K. STECHER G. PETERSON D. FILIPSKI A. KUMAR S. MEGA6: MOLECULAR EVOLUTIONARY GENETICS ANALYSIS VERSION 6.0 (2013) 942 945
MURRELL B. WERTHEIM J.O. MOOLA S. WEIGHILL T. SCHEFFLER K. KOSAKOVSKY POND S.L. DETECTING INDIVIDUAL SITES SUBJECT TO EPISODIC DIVERSIFYING SELECTI… 905 909
YANG Z. PAML 4: PHYLOGENETIC ANALYSIS BY MAXIMUM LIKELIHOOD (2007) 644 651
POND S.L.K. FROST S.D.W. MUSE S.V. HYPHY: HYPOTHESIS TESTING USING PHYLOGENIES (2005) 533 533
EDGAR R.C. MUSCLE: MULTIPLE SEQUENCE ALIGNMENT WITH HIGH ACCURACY AND HIGH THROUGHPUT (2004) 457 519
POND S.L. FROST S.D. MUSE S.V. HYPHY: HYPOTHESIS TESTING USING PHYLOGENIES (2005) 453 453
KINDE I. WU J. PAPADOPOULOS N. KINZLER K.W. VOGELSTEIN B. DETECTION AND QUANTIFICATION OF RARE MUTATIONS WITH MASSIVELY PARALLEL SEQUENCING (2011) 427 549
MARTIN D.P. MURRELL B. GOLDEN M. KHOOSAL A. MUHIRE B. RDP4: DETECTION AND ANALYSIS OF RECOMBINATION PATTERNS IN VIRUS GENOMES (2015) 356 356
DRUMMOND A.J. SUCHARD M.A. XIE D. RAMBAUT A. BAYESIAN PHYLOGENETICS WITH BEAUTI AND THE BEAST 1.7 (2012) 346 346
MURRELL B. MOOLA S. MABONA A. WEIGHILL T. SHEWARD D. KOSAKOVSKY POND S.L. SCHEFFLER K. FUBAR: A FAST UNCONSTRAINED BAYESIAN APPROXIMATION FOR INFER… 342 342

Development of Knowledge Bases

Technical description

In a co-cittion network, the strength of the relationship between a reference pair \(m\) and \(n\) (\(s_{m,n}^{coc}\)) is expressed by the number of publications \(C\) which are jointly citing reference \(m\) and \(n\).

\[s_{m,n}^{coc} = \sum_i c_{i,m} c_{i,n}\]

The intuition here is that references which are frequently cited together are likely to share commonalities in theory, topic, methodology, or context. It can be interpreted as a measure of similarity as evaluated by other researchers that decide to jointly cite both references. Because the publication process is time-consuming, co-citation is a backward-looking measure, which is appropriate to map the relationship between core literature of a field.

Research Areas: Bibliographic coupling analysis

Research Areas main summary

This is arguably the more interesting part. Here, we identify the literature’s current knowledge frontier by carrying out a bibliographic coupling analysis of the publications in our corpus. This measure uses bibliographical information of publications to establish a similarity relationship between them. Again, method details to be found in the tab Technical description. As you will see, we identify the main research area, but also a set of adjacent research areas with some theoretical/methodological/application overlap.

To identify communities in the field’s knowledge frontier (labeled research areas) we again use the Lovain Algorithm (Blondel et al., 2008). We identify the following communities = research areas.

label AU PY TI dgr_int TC TC_year
Research Area 1: RA 1: unlabeled (n = 1157, density =0.1)
RA 1: unlabeled SICHERER SH;SAMPSON HA 2018 FOOD ALLERGY: A REVIEW AND UPDATE ON EPIDEMIOLOGY, PATHOGENESIS, DIAGNOSIS, PREVENTION, AND MANAGEMENT 5.26 659 164.75
RA 1: unlabeled VICKERY BP;VEREDA A;CA… 2018 AR101 ORAL IMMUNOTHERAPY FOR PEANUT ALLERGY 4.46 291 72.75
RA 1: unlabeled TOGIAS A;COOPER SF;ACE… 2017 ADDENDUM GUIDELINES FOR THE PREVENTION OF PEANUT ALLERGY IN THE UNITED STATES: REPORT OF THE NATIONAL INSTITUTE OF ALLERGY… 4.87 246 49.20
RA 1: unlabeled PAJNO GB;FERNANDEZ-RIV… 2018 EAACI GUIDELINES ON ALLERGEN IMMUNOTHERAPY: IGE-MEDIATED FOOD ALLERGY 2.95 249 62.25
RA 1: unlabeled MATRICARDI PM;KLEINE-T… 2016 EAACI MOLECULAR ALLERGOLOGY USER’S GUIDE 1.38 507 84.50
RA 1: unlabeled BIRD JA;SPERGEL JM;JON… 2018 EFFICACY AND SAFETY OF AR101 IN ORAL IMMUNOTHERAPY FOR PEANUT ALLERGY: RESULTS OF ARC001, A RANDOMIZED, DOUBLE-BLIND, PLAC… 5.93 105 26.25
RA 1: unlabeled GUPTA RS;WARREN CM;SMI… 2018 THE PUBLIC HEALTH IMPACT OF PARENT-REPORTED CHILDHOOD FOOD ALLERGIES IN THE UNITED STATES 2.50 249 62.25
RA 1: unlabeled WOOD RA 2016 FOOD ALLERGEN IMMUNOTHERAPY: CURRENT STATUS AND PROSPECTS FOR THE FUTURE 4.31 139 23.17
RA 1: unlabeled EBISAWA M;ITO K;FUJISA… 2017 JAPANESE GUIDELINES FOR FOOD ALLERGY 2017 3.69 162 32.40
RA 1: unlabeled NURMATOV U;DHAMI S;ARA… 2017 ALLERGEN IMMUNOTHERAPY FOR IGE-MEDIATED FOOD ALLERGY: A SYSTEMATIC REVIEW AND META-ANALYSIS 1.99 241 48.20
Research Area 2: RA 2: unlabeled (n = 755, density =0.12)
RA 2: unlabeled TURECKI G;MEANEY MJ 2016 EFFECTS OF THE SOCIAL ENVIRONMENT AND STRESS ON GLUCOCORTICOID RECEPTOR GENE METHYLATION: A SYSTEMATIC REVIEW 3.95 373 62.17
RA 2: unlabeled YEHUDA R;DASKALAKIS NP… 2016 HOLOCAUST EXPOSURE INDUCED INTERGENERATIONAL EFFECTS ON FKBP5 METHYLATION 2.57 339 56.50
RA 2: unlabeled BAUMEISTER D;AKHTAR R;… 2016 CHILDHOOD TRAUMA AND ADULTHOOD INFLAMMATION: A META-ANALYSIS OF PERIPHERAL C-REACTIVE PROTEIN, INTERLEUKIN-6 AND TUMOUR NE… 1.62 489 81.50
RA 2: unlabeled NEMEROFF CB 2016 PARADISE LOST: THE NEUROBIOLOGICAL AND CLINICAL CONSEQUENCES OF CHILD ABUSE AND NEGLECT 1.92 341 56.83
RA 2: unlabeled NESTLER EJ;PEÑA CJ;KUN… 2016 EPIGENETIC BASIS OF MENTAL ILLNESS 2.37 180 30.00
RA 2: unlabeled BERENS AE;JENSEN SKG;N… 2017 BIOLOGICAL EMBEDDING OF CHILDHOOD ADVERSITY: FROM PHYSIOLOGICAL MECHANISMS TO CLINICAL IMPLICATIONS 1.70 207 41.40
RA 2: unlabeled TYRKA AR;PARADE SH;WEL… 2016 METHYLATION OF THE LEUKOCYTE GLUCOCORTICOID RECEPTOR GENE PROMOTER IN ADULTS: ASSOCIATIONS WITH EARLY ADVERSITY AND DEPRES… 4.02 79 13.17
RA 2: unlabeled BOWERS ME;YEHUDA R 2016 INTERGENERATIONAL TRANSMISSION OF STRESS IN HUMANS 1.25 220 36.67
RA 2: unlabeled HOUTEPEN LC;VINKERS CH… 2016 GENOME-WIDE DNA METHYLATION LEVELS AND ALTERED CORTISOL STRESS REACTIVITY FOLLOWING CHILDHOOD TRAUMA IN HUMANS 1.90 130 21.67
RA 2: unlabeled BUSTAMANTE AC;AIELLO A… 2016 GLUCOCORTICOID RECEPTOR DNA METHYLATION, CHILDHOOD MALTREATMENT AND MAJOR DEPRESSION 3.92 61 10.17
Research Area 3: RA 3: unlabeled (n = 733, density =0.12)
RA 3: unlabeled ZHENG Y;QIN L;ZACARÍAS… 2016 STRUCTURE OF CC CHEMOKINE RECEPTOR 2 WITH ORTHOSTERIC AND ALLOSTERIC ANTAGONISTS 2.46 165 27.50
RA 3: unlabeled OSWALD C;RAPPAS M;KEAN… 2016 INTRACELLULAR ALLOSTERIC ANTAGONISM OF THE CCR9 RECEPTOR 2.13 142 23.67
RA 3: unlabeled THAL DM;GLUKHOVA A;SEX… 2018 STRUCTURAL INSIGHTS INTO G-PROTEIN-COUPLED RECEPTOR ALLOSTERY 1.82 149 37.25
RA 3: unlabeled SMITH JS;LEFKOWITZ RJ;… 2018 BIASED SIGNALLING: FROM SIMPLE SWITCHES TO ALLOSTERIC MICROPROCESSORS 0.78 316 79.00
RA 3: unlabeled SCHNEIDMAN-DUHOVNY D;H… 2016 FOXS, FOXSDOCK AND MULTIFOXS: SINGLE-STATE AND MULTI-STATE STRUCTURAL MODELING OF PROTEINS AND THEIR COMPLEXES BASED ON SA… 0.89 236 39.33
RA 3: unlabeled JANSON G;ZHANG C;PRADO… 2017 PYMOD 2.0: IMPROVEMENTS IN PROTEIN SEQUENCE-STRUCTURE ANALYSIS AND HOMOLOGY MODELING WITHIN PYMOL 1.88 110 22.00
RA 3: unlabeled ZHOU Q;YANG D;WU M;GUO… 2019 COMMON ACTIVATION MECHANISM OF CLASS A GPCRS 1.62 112 37.33
RA 3: unlabeled LIU X;AHN S;KAHSAI AW;… 2017 MECHANISM OF INTRACELLULAR ALLOSTERIC Β 2 AR ANTAGONIST REVEALED BY X-RAY CRYSTAL STRUCTURE 1.81 94 18.80
RA 3: unlabeled YEN H-Y;HOI KK;LIKO I;… 2018 PTDINS(4,5)P2 STABILIZES ACTIVE STATES OF GPCRS AND ENHANCES SELECTIVITY OF G-PROTEIN COUPLING 1.31 129 32.25
RA 3: unlabeled ROBERTSON N;RAPPAS M;D… 2018 STRUCTURE OF THE COMPLEMENT C5A RECEPTOR BOUND TO THE EXTRA-HELICAL ANTAGONIST NDT9513727 2.36 64 16.00
Research Area 4: RA 4: unlabeled (n = 679, density =0.15)
RA 4: unlabeled HUGHES CE;NIBBS RJB 2018 A GUIDE TO CHEMOKINES AND THEIR RECEPTORS 2.03 313 78.25
RA 4: unlabeled POZZOBON T;GOLDONI G;V… 2016 CXCR4 SIGNALING IN HEALTH AND DISEASE 4.84 122 20.33
RA 4: unlabeled JANSSENS R;STRUYF S;PR… 2018 THE UNIQUE STRUCTURAL AND FUNCTIONAL FEATURES OF CXCL12 3.83 120 30.00
RA 4: unlabeled GUO F;WANG Y;LIU J;MOK… 2016 CXCL12/CXCR4: A SYMBIOTIC BRIDGE LINKING CANCER CELLS AND THEIR STROMAL NEIGHBORS IN ONCOGENIC COMMUNICATION NETWORKS 1.35 232 38.67
RA 4: unlabeled POETA VM;MASSARA M;CAP… 2019 CHEMOKINES AND CHEMOKINE RECEPTORS: NEW TARGETS FOR CANCER IMMUNOTHERAPY 1.54 204 68.00
RA 4: unlabeled STONE MJ;HAYWARD JA;HU… 2017 MECHANISMS OF REGULATION OF THE CHEMOKINE-RECEPTOR NETWORK 2.19 134 26.80
RA 4: unlabeled LIM SY;YUZHALIN AE;GOR… 2016 TARGETING THE CCL2-CCR2 SIGNALING AXIS IN CANCER METASTASIS 0.90 260 43.33
RA 4: unlabeled TOKUNAGA R;ZHANG W;NAS… 2018 CXCL9, CXCL10, CXCL11/CXCR3 AXIS FOR IMMUNE ACTIVATION – A TARGET FOR NOVEL CANCER THERAPY 0.50 420 105.00
RA 4: unlabeled BONECCHI R;GRAHAM GJ 2016 ATYPICAL CHEMOKINE RECEPTORS AND THEIR ROLES IN THE RESOLUTION OF THE INFLAMMATORY RESPONSE 2.42 86 14.33
RA 4: unlabeled HAUSER MA;LEGLER DF 2016 COMMON AND BIASED SIGNALING PATHWAYS OF THE CHEMOKINE RECEPTOR CCR7 ELICITED BY ITS LIGANDS CCL19 AND CCL21 IN LEUKOCYTES 2.03 102 17.00
Research Area 5: RA 5: unlabeled (n = 675, density =0.13)
RA 5: unlabeled YU G;SMITH DK;ZHU H;GU… 2017 GGTREE: AN R PACKAGE FOR VISUALIZATION AND ANNOTATION OF PHYLOGENETIC TREES WITH THEIR COVARIATES AND OTHER ASSOCIATED DATA 1.17 1324 264.80
RA 5: unlabeled GOODWIN S;MCPHERSON JD… 2016 COMING OF AGE: TEN YEARS OF NEXT-GENERATION SEQUENCING TECHNOLOGIES 0.45 1917 319.50
RA 5: unlabeled JENNINGS LJ;ARCILA ME;… 2017 GUIDELINES FOR VALIDATION OF NEXT-GENERATION SEQUENCING–BASED ONCOLOGY PANELS: A JOINT CONSENSUS RECOMMENDATION OF THE ASS… 1.02 319 63.80
RA 5: unlabeled HEATHER JM;CHAIN B 2016 THE SEQUENCE OF SEQUENCERS: THE HISTORY OF SEQUENCING DNA 0.64 483 80.50
RA 5: unlabeled BENVENUTO D;GIOVANETTI… 2020 THE 2019-NEW CORONAVIRUS EPIDEMIC: EVIDENCE FOR VIRUS EVOLUTION 0.80 370 185.00
RA 5: unlabeled SALK JJ;SCHMITT MW;LOE… 2018 ENHANCING THE ACCURACY OF NEXT-GENERATION SEQUENCING FOR DETECTING RARE AND SUBCLONAL MUTATIONS 1.27 219 54.75
RA 5: unlabeled FRANZO G;CORTEY M;SEGA… 2016 PHYLODYNAMIC ANALYSIS OF PORCINE CIRCOVIRUS TYPE 2 REVEALS GLOBAL WAVES OF EMERGING GENOTYPES AND THE CIRCULATION OF RECOM… 2.28 100 16.67
RA 5: unlabeled GAO F;CHEN C;ARAB DA;D… 2019 EASYCODEML: A VISUAL TOOL FOR ANALYSIS OF SELECTION USING CODEML 1.82 123 41.00
RA 5: unlabeled WEAVER S;SHANK SD;SPIE… 2018 DATAMONKEY 2.0: A MODERN WEB APPLICATION FOR CHARACTERIZING SELECTIVE AND OTHER EVOLUTIONARY PROCESSES 0.78 285 71.25
RA 5: unlabeled WANG L-G;LAM TT-Y;XU S… 2020 TREEIO: AN R PACKAGE FOR PHYLOGENETIC TREE INPUT AND OUTPUT WITH RICHLY ANNOTATED AND ASSOCIATED DATA 1.80 96 48.00
Research Area 6: RA 6: unlabeled (n = 563, density =0.32)
RA 6: unlabeled O’NEILL LAJ;KISHTON RJ… 2016 A GUIDE TO IMMUNOMETABOLISM FOR IMMUNOLOGISTS 2.37 1210 201.67
RA 6: unlabeled BUCK MD;SOWELL RT;KAEC… 2017 METABOLIC INSTRUCTION OF IMMUNITY 3.54 535 107.00
RA 6: unlabeled SUKUMAR M;LIU J;MEHTA … 2016 MITOCHONDRIAL MEMBRANE POTENTIAL IDENTIFIES CELLS WITH ENHANCED STEMNESS FOR CELLULAR THERAPY 6.50 196 32.67
RA 6: unlabeled KISHTON RJ;SUKUMAR M;R… 2017 METABOLIC REGULATION OF T CELL LONGEVITY AND FUNCTION IN TUMOR IMMUNOTHERAPY 5.16 187 37.40
RA 6: unlabeled JOHNSON MO;WOLF MM;MAD… 2018 DISTINCT REGULATION OF TH17 AND TH1 CELL DIFFERENTIATION BY GLUTAMINASE-DEPENDENT METABOLISM 3.84 231 57.75
RA 6: unlabeled LOFTUS RM;FINLAY DK 2016 IMMUNOMETABOLISM: CELLULAR METABOLISM TURNS IMMUNE REGULATOR 3.18 229 38.17
RA 6: unlabeled ALMEIDA L;LOCHNER M;BE… 2016 METABOLIC PATHWAYS IN T CELL ACTIVATION AND LINEAGE DIFFERENTIATION 2.95 211 35.17
RA 6: unlabeled MENK AV;SCHARPING NE;M… 2018 EARLY TCR SIGNALING INDUCES RAPID AEROBIC GLYCOLYSIS ENABLING DISTINCT ACUTE T CELL EFFECTOR FUNCTIONS 3.45 174 43.50
RA 6: unlabeled NEWTON R;PRIYADHARSHIN… 2016 IMMUNOMETABOLISM OF REGULATORY T CELLS 3.13 190 31.67
RA 6: unlabeled BANTUG GR;GALLUZZI L;K… 2018 THE SPECTRUM OF T CELL METABOLISM IN HEALTH AND DISEASE 2.97 200 50.00
Research Area 7: RA 7: unlabeled (n = 490, density =0.26)
RA 7: unlabeled SMITH T;HEGER A;SUDBERY I 2017 UMI-TOOLS: MODELING SEQUENCING ERRORS IN UNIQUE MOLECULAR IDENTIFIERS TO IMPROVE QUANTIFICATION ACCURACY 0.76 459 91.80
RA 7: unlabeled TURCHANINOVA MA;DAVYDO… 2016 HIGH-QUALITY FULL-LENGTH IMMUNOGLOBULIN PROFILING WITH UNIQUE MOLECULAR BARCODING 3.28 100 16.67
RA 7: unlabeled BREDEN F;LUNING PRAK E… 2017 REPRODUCIBILITY AND REUSE OF ADAPTIVE IMMUNE RECEPTOR REPERTOIRE DATA 5.81 54 10.80
RA 7: unlabeled MIHO E;YERMANOS A;WEBE… 2018 COMPUTATIONAL STRATEGIES FOR DISSECTING THE HIGH-DIMENSIONAL COMPLEXITY OF ADAPTIVE IMMUNE REPERTOIRES 3.85 81 20.25
RA 7: unlabeled ROSATI E;DOWDS CM;LIAS… 2017 OVERVIEW OF METHODOLOGIES FOR T-CELL RECEPTOR REPERTOIRE ANALYSIS 2.58 119 23.80
RA 7: unlabeled RALPH DK;MATSEN FA;IV 2016 CONSISTENCY OF VDJ REARRANGEMENT AND SUBSTITUTION PARAMETERS ENABLES ACCURATE B CELL RECEPTOR SEQUENCE ANNOTATION 4.06 66 11.00
RA 7: unlabeled GREIFF V;MENZEL U;MIHO… 2017 SYSTEMS ANALYSIS REVEALS HIGH GENETIC AND ANTIGEN-DRIVEN PREDETERMINATION OF ANTIBODY REPERTOIRES THROUGHOUT B CELL DEVELO… 3.82 69 13.80
RA 7: unlabeled GREIFF V;WEBER CR;PALM… 2017 LEARNING THE HIGH-DIMENSIONAL IMMUNOGENOMIC FEATURES THAT PREDICT PUBLIC AND PRIVATE ANTIBODY REPERTOIRES 4.47 55 11.00
RA 7: unlabeled DEWITT WS;LINDAU P;SNY… 2016 A PUBLIC DATABASE OF MEMORY AND NAIVE B-CELL RECEPTOR SEQUENCES 3.52 68 11.33
RA 7: unlabeled LIU X;WU J 2018 HISTORY, APPLICATIONS, AND CHALLENGES OF IMMUNE REPERTOIRE RESEARCH 6.12 36 9.00
Research Area 8: RA 8: unlabeled (n = 481, density =0.42)
RA 8: unlabeled PAVLOVA NN;THOMPSON CB 2016 THE EMERGING HALLMARKS OF CANCER METABOLISM 3.17 2449 408.17
RA 8: unlabeled DE BERARDINIS RJ;CHAND… 2016 FUNDAMENTALS OF CANCER METABOLISM 3.21 1236 206.00
RA 8: unlabeled DUCKER GS;RABINOWITZ JD 2017 ONE-CARBON METABOLISM IN HEALTH AND DISEASE 5.55 697 139.40
RA 8: unlabeled VANDER HEIDEN MG;DEBER… 2017 UNDERSTANDING THE INTERSECTIONS BETWEEN METABOLISM AND CANCER BIOLOGY 3.81 936 187.20
RA 8: unlabeled YANG M;VOUSDEN KH 2016 SERINE AND ONE-CARBON METABOLISM IN CANCER 4.57 417 69.50
RA 8: unlabeled NEWMAN AC;MADDOCKS ODK 2017 ONE-CARBON METABOLISM IN CANCER 9.19 181 36.20
RA 8: unlabeled LUENGO A;GUI DY;VANDER… 2017 TARGETING METABOLISM FOR CANCER THERAPY 3.95 383 76.60
RA 8: unlabeled MATTAINI KR;SULLIVAN M… 2016 THE IMPORTANCE OF SERINE METABOLISM IN CANCER 7.42 184 30.67
RA 8: unlabeled MA EH;BANTUG G;GRISS T… 2017 SERINE IS AN ESSENTIAL METABOLITE FOR EFFECTOR T CELL EXPANSION 4.42 256 51.20
RA 8: unlabeled GAO X;LEE K;REID MA;SA… 2018 SERINE AVAILABILITY INFLUENCES MITOCHONDRIAL DYNAMICS AND FUNCTION THROUGH LIPID METABOLISM 10.38 96 24.00
Research Area 9: RA 9: unlabeled (n = 463, density =0.78)
RA 9: unlabeled CHINEN T;KANNAN AK;LEV… 2016 AN ESSENTIAL ROLE FOR THE IL-2 RECEPTOR IN T REG CELL FUNCTION 7.04 376 62.67
RA 9: unlabeled KAMADA T;TOGASHI Y;TAY… 2019 PD-1+ REGULATORY T CELLS AMPLIFIED BY PD-1 BLOCKADE PROMOTE HYPERPROGRESSION OF CANCER 6.30 345 115.00
RA 9: unlabeled TOGASHI Y;SHITARA K;NI… 2019 REGULATORY T CELLS IN CANCER IMMUNOSUPPRESSION — IMPLICATIONS FOR ANTICANCER THERAPY 4.73 417 139.00
RA 9: unlabeled DOMINGUEZ-VILLAR M;HAF… 2018 REGULATORY T CELLS IN AUTOIMMUNE DISEASE 7.25 271 67.75
RA 9: unlabeled MAJ T;WANG W;CRESPO J;… 2017 OXIDATIVE STRESS CONTROLS REGULATORY T CELL APOPTOSIS AND SUPPRESSOR ACTIVITY AND PD-L1-BLOCKADE RESISTANCE IN TUMOR 5.14 332 66.40
RA 9: unlabeled LI MO;RUDENSKY AY 2016 T CELL RECEPTOR SIGNALLING IN THE CONTROL OF REGULATORY T CELL DIFFERENTIATION AND FUNCTION 6.23 262 43.67
RA 9: unlabeled WING JB;TANAKA A;SAKAG… 2019 HUMAN FOXP3 + REGULATORY T CELL HETEROGENEITY AND FUNCTION IN AUTOIMMUNITY AND CANCER 6.47 233 77.67
RA 9: unlabeled PLITAS G;RUDENSKY AY 2016 REGULATORY T CELLS: DIFFERENTIATION AND FUNCTION 10.84 139 23.17
RA 9: unlabeled TAKEUCHI Y;NISHIKAWA H 2016 ROLES OF REGULATORY T CELLS IN CANCER IMMUNITY 5.13 277 46.17
RA 9: unlabeled KITAGAWA Y;OHKURA N;KI… 2017 GUIDANCE OF REGULATORY T CELL DEVELOPMENT BY SATB1-DEPENDENT SUPER-ENHANCER ESTABLISHMENT 7.09 178 35.60

Development

Connectivity between the research areas

Technical description

In a bibliographic coupling network, the coupling-strength between publications is determined by the number of commonly cited references they share, assuming a common pool of references to indicate similarity in context, methods, or theory. Formally, the strength of the relationship between a publication pair \(i\) and \(j\) (\(s_{i,j}^{bib}\)) is expressed by the number of commonly cited references.

\[s_{i,j}^{bib} = \sum_m c_{i,m} c_{j,m}\]

Since our corpus contains publications which differ strongly in terms of the number of cited references, we normalize the coupling strength by the Jaccard similarity coefficient. Here, we weight the intercept of two publications’ bibliography (shared refeences) by their union (number of all references cited by either \(i\) or \(j\)). It is bounded between zero and one, where one indicates the two publications to have an identical bibliography, and zero that they do not share any cited reference. Thereby, we prevent publications from having high coupling strength due to a large bibliography (e.g., literature surveys).

\[S_{i,j}^{jac-bib} =\frac{C(i \cap j)}{C(i \cup j)} = \frac{s_{i,j}^{bib}}{c_i + c_j - s_{i,j}^{bib}}\]

More recent articles have a higher pool of possible references to co-cite to, hence they are more likely to be coupled. Consequently, bibliographic coupling represents a forward looking measure, and the method of choice to identify the current knowledge frontier at the point of analysis.

Knowledge Bases, Research Areas & Topics Interaction

Endnotes

All results are preliminary so far…